Field
Embodiments of the present disclosure generally relates to semiconductor manufacturing, and, more specifically, embodiments of the present disclosure relate to anomaly detection in sensor data retrieved during semiconductor processing.
Description of the Related Art
Manufacturing of electronic devices typically involves performing a sequence of procedures with respect to a substrate such as a silicon substrate, a glass plate, etc. (Such substrates may also be referred to as wafers, whether patterned or unpatterned.) These steps may include polishing, deposition, etching, photolithography, heat treatment, and so forth. Usually a number of different processing steps may be performed in a single processing system or “tool” which includes a plurality of processing chambers. During processing, each chamber in which a procedure is carried out may include a plurality of sensors, with each sensor configured to monitor a predefined metric relating to substrate processing.
Anomaly detection in sensor trace data aids in assessing the overall health of the chamber in which a substrate processing procedure is carried forth. Some technique for anomaly detection in sensor trace data is recipe dependent, i.e., a different method for detecting anomalies in sensor trace data is needed based on the tool used and the process run. As a result, different techniques are needed, which can be costly and time consuming to develop. Therefore, there is a continual need for an improved method of detecting anomalies in sensor data retrieved during semiconductor processing.